Top Senior Data Engineer Jobs in Atlanta, GA

Design, implement, and manage advanced data ecosystems and scalable ETL/ELT pipelines. Analyze complex problems, deliver data warehousing and governance solutions, mentor junior staff, and build client relationships while maintaining high standards and business-context awareness.

Lead design and implementation of enterprise data architecture and cloud-based data solutions. Manage large data engineering projects, develop data models and pipelines, ensure governance and security compliance, advise clients strategically, and build high-performing inclusive teams.

Lead design and implementation of data architecture, ETL/ELT pipelines, data models, warehouses and lakes. Ensure data governance, security, cloud deployments, performance and cost optimization. Coach and manage team members, partner with stakeholders, and drive data-driven solutions for clients.

Design and implement data architecture and scalable ETL/ELT pipelines on cloud platforms (AWS/Azure/GCP). Analyze complex problems, mentor junior staff, ensure data governance/security compliance, liaise with stakeholders, and deliver high-quality client solutions while developing technical and client-facing skills.

Build and maintain centralized pricing data infrastructure, scalable workflows, and data pipelines; integrate AI capabilities; deliver pricing tools, reporting, and governance to support data-driven pricing and budgeting across the firm.

Lead architecture and delivery of cloud data platforms, design scalable data warehouse and lake solutions, implement ETL/ELT frameworks, optimize platform performance and resilience, champion automation, governance, and mentor engineering teams to deliver enterprise analytics and data products.

Design, build, and maintain enterprise analytics solutions, semantic models, and reporting datasets using Microsoft Fabric, Databricks, SQL, Python, and BI tools. Lead data modeling, data quality, CI/CD, and performance optimization; translate business requirements into scalable analytics; mentor engineers and collaborate with architects and stakeholders to deliver trusted, self-service and executive reporting across the Americas.

Lead design and implementation of scalable data pipelines and models for CX analytics. Integrate structured and unstructured sources (DB2, SQL Server, Teradata, Web APIs), enable AI/LLM workflows, define data engineering standards, mentor engineers, and partner with data scientists and BI to deliver reliable analytics and automation.

Designs, builds, and maintains scalable data infrastructure, streaming and batch pipelines, and data products. Works with stakeholders to model, transform, and deploy data solutions using cloud, streaming, and ETL frameworks while ensuring governance, observability, and automated CI/CD deployments.

Designs and implements scalable cloud-based data pipelines and architectures, defines technical scope with stakeholders, monitors production reliability, mentors junior engineers, collaborates with data scientists and analysts, and creates reusable best practices and assets to deliver trusted data for decision-making.

Lead development and delivery of data engineering solutions for clients: design data architectures, build and maintain ETL pipelines, apply advanced analytics, implement BI visualizations, coach teams, manage managed-services SLAs, and engage stakeholders to validate and refine outcomes.

Lead data engineering engagements delivering ETL/ELT solutions, pipelines, and cloud analytics. Build and maintain architectures (DataStage, AWS/Redshift, DB2/SQL Server, GoldenGate/CDC, S3/Glue), oversee BI and visualization, manage client accounts and teams, mentor junior staff, ensure project delivery and quality, and drive process and technology adoption.

Build, operate, and monitor ETL/ELT pipelines between marketing, sales, and operational systems into Databricks. Implement dimensional models, identity resolution, data quality checks, API integrations, and scheduled/event-driven syncs to support segmentation, attribution, and campaign activation. Maintain documentation, alerting, and runbooks.

Lead design, build, and maintain scalable data pipelines, ETL processes, data models, and storage solutions. Support production data ecosystem, optimize performance, ensure data quality and security, integrate data sources/APIs, and provide technical guidance to teams while collaborating with stakeholders.

Design, build, and maintain data warehouses, data marts, and OLAP solutions; develop ETL frameworks, data models, SSIS/SSAS/SSRS artifacts, and performance-tuned SQL Server databases to support analytics and visualization projects.

Design and codify enterprise streaming (Kappa) architectures on Microsoft Fabric and Kafka. Build reusable frameworks, replay/backfill patterns, idempotent processing, schema-drift handling, monitoring dashboards, and templates to enable standardized, production-grade real-time pipelines and developer-friendly streaming frameworks.

Lead the design and migration of a data platform architecture. Manage data pipelines, mentor teams, and ensure platform reliability.

Design, build, and maintain end-to-end data pipelines and models for CX analytics. Integrate structured and unstructured sources, support BI and AI/LLM-enabled workflows, optimize performance and scalability, mentor junior engineers, and collaborate with data scientists and business partners to deliver reliable, automated analytics solutions.

Design and build scalable data lakes, warehouses, and lakehouse architectures. Implement Python ETL/ELT pipelines, orchestrate workflows with Airflow, ingest third-party APIs, optimize columnar formats, and support ML initiatives using Spark, Snowflake, and AWS. Act as technical consultant translating business needs into data architecture roadmaps.

Design, develop, and support Big Data solutions on Teradata Aster and Hadoop platforms. Build ETL pipelines, data mining, reporting, and predictive analytics; write efficient code for large/unstructured datasets; translate business use cases to production; mentor users; contribute to Big Data roadmap and standards.

The Sr. ETL Informatica Systems Engineer develops ETL applications for the EDW/BI program using Informatica tools, managing complex SQL and APIs.

Design, build, and optimize enterprise data foundations, ETL/ELT pipelines, data models, and migrations. Ensure data quality, governance, and secure integrations across financial, practice-management, CRM, and operational systems to support reporting, automation, and AI initiatives.

Design, build, and operationalize Databricks-based cloud data lakehouse solutions. Develop dbt transformation pipelines, implement CI/CD with Azure DevOps, apply IaC (Terraform), optimize database performance, participate in code reviews, and lead delivery planning for a squad of data engineers in Agile ceremonies.

Lead architect and hands‑on senior data engineer who designs scalable data platforms and medallion architectures, optimizes ETL/ELT and data modeling, implements CI/CD and IaC, enforces data governance and security, mentors engineers, integrates BI tools, and leads client-facing technical engagements.

The Information Management Engineer will oversee metadata management, master data models, integration pipelines, and data governance efforts, primarily utilizing Azure and GCP platforms.